Tätigkeitsbereich:IT/Telekommunikation
Fachabteilung:Engineering Systems
Gesellschaft:Mercedes-Benz Research and Development India Private Limited
Standort:Mercedes-Benz Research and Development India Private Limited, Bangalore
Startdatum:01.12.2026
Veröffentlichungsdatum:11.11.2026
Stellennummer:MER0004AAS
Arbeitszeit:Vollzeit
Aufgaben
Description - ExternalJob Description: AI Engineer (1-4 Years Overall Experience)
Location: Bengaluru
Employment Type: Full-Time
Role Purpose The AI Engineer will design, develop and integrate AI-enabled capabilities into enterprise and manufacturing applications. The role will focus on Generative AI, intelligent automation, data integration and AI-assisted software engineering while building strong foundations in production-grade AI engineering.
The engineer will work with senior engineers and architects to convert manufacturing and business use cases into scalable AI solutions.
Key Responsibilities1. Generative AI & Agentic Solutions
- Develop applications using LLMs and Generative AI.
- Build RAG-based solutions using enterprise documents and structured/unstructured data.
- Develop AI agents and tool-based workflows for engineering and business processes.
- Implement prompt engineering, structured outputs and function/tool calling.
- Evaluate AI responses for accuracy, relevance and reliability.
1. AI Application Engineering
- Develop APIs and backend services using Python and FastAPI.
- Integrate AI capabilities into existing enterprise applications.
- Build reusable AI services/components rather than standalone prototypes.
- Develop proof-of-concepts and mature them toward production solutions.
- Write clean, modular and testable code.
1. Data & Knowledge Integration
- Connect AI solutions with enterprise databases, APIs, documents and engineering systems.
- Implement document ingestion, chunking, embedding and retrieval pipelines.
- Work with SQL, REST APIs, JSON and structured/unstructured datasets.
- Exposure to vector databases/search technologies such as Azure AI Search, PostgreSQL/pgvector or equivalent.
1. AI-Native Software Engineering
- Use AI coding assistants effectively across development, testing and documentation.
- Build automated unit and integration tests.
- Participate in code reviews and engineering quality practices.
- Work with Git, CI/CD, containers and DevSecOps pipelines.
- Contribute to reusable engineering accelerators and automation.
1. Manufacturing AI Use Cases
Work with domain experts to develop solutions such as:
- Engineering knowledge assistants
- Manufacturing/planning copilots
- Intelligent document processing
- Automated engineering workflows
- Semantic enterprise search
- AI-assisted validation and testing
- Data-driven recommendations
- Agent-based process automation
Required Skills Must-have
- Bachelor's/Master's degree in Computer Science, AI, Data Science, Information Technology or related engineering discipline
- Strong programming fundamentals in Python
- Understanding of REST APIs and backend application development
- Fundamentals of Generative AI and LLMs
- Understanding of RAG, embeddings and vector search
- Working knowledge of SQL and data handling
- Git and modern software-development practices
- Strong analytical and problem-solving skills
Good-to-have
- Azure AI / cloud services
- FastAPI
- Azure OpenAI or equivalent LLM platforms
- Azure AI Search
- LangChain / Semantic Kernel or similar orchestration frameworks
- Docker / Kubernetes
- CI/CD and DevSecOps
- React/Angular knowledge
- ML/MLflow/MLOps fundamentals
- Knowledge graphs
- Agentic AI / multi-agent concepts
Qualifikationen Description - ExternalJob Description: AI Engineer (1-4 Years Overall Experience)
Location: Bengaluru
Employment Type: Full-Time
Role Purpose The AI Engineer will design, develop and integrate AI-enabled capabilities into enterprise and manufacturing applications. The role will focus on Generative AI, intelligent automation, data integration and AI-assisted software engineering while building robust foundations in production-grade AI engineering.
The engineer will work with senior engineers and architects to convert manufacturing and business use cases into scalable AI solutions.
Key Responsibilities1. Generative AI & Agentic Solutions
- Develop applications using LLMs and Generative AI.
- Build RAG-based solutions using enterprise documents and structured/unstructured data.
- Develop AI agents and tool-based workflows for engineering and business processes.
- Implement prompt engineering, structured outputs and function/tool calling.
- Evaluate AI responses for accuracy, relevance and reliability.
1. AI Application Engineering
- Develop APIs and backend services using Python and FastAPI.
- Integrate AI capabilities into existing enterprise applications.
- Build reusable AI services/components rather than standalone prototypes.
- Develop proof-of-concepts and mature them toward production solutions.
- Write clean, modular and testable code.
1. Data & Knowledge Integration
- Connect AI solutions with enterprise databases, APIs, documents and engineering systems.
- Implement document ingestion, chunking, embedding and retrieval pipelines.
- Work with SQL, REST APIs, JSON and structured/unstructured datasets.
- Exposure to vector databases/search technologies such as Azure AI Search, PostgreSQL/pgvector or equivalent.
1. AI-Native Software Engineering
- Use AI coding assistants effectively across development, testing and documentation.
- Build automated unit and integration tests.
- Participate in code reviews and engineering quality practices.
- Work with Git, CI/CD, containers and DevSecOps pipelines.
- Contribute to reusable engineering accelerators and automation.
1. Manufacturing AI Use Cases
Work with domain experts to develop solutions such as:
- Engineering knowledge assistants
- Manufacturing/planning copilots
- Intelligent document processing
- Automated engineering workflows
- Semantic enterprise search
- AI-assisted validation and testing
- Data-driven recommendations
- Agent-based process automation
Required Skills Must-have
- Bachelor's/Master's degree in Computer Science, AI, Data Science, Information Technology or related engineering discipline
- Strong programming fundamentals in Python
- Understanding of REST APIs and backend application development
- Fundamentals of Generative AI and LLMs
- Understanding of RAG, embeddings and vector search
- Working knowledge of SQL and data handling
- Git and modern software-development practices
- Strong analytical and problem-solving skills
Good-to-have
- Azure AI / cloud services
- FastAPI
- Azure OpenAI or equivalent LLM platforms
- Azure AI Search
- LangChain / Semantic Kernel or similar orchestration frameworks
- Docker / Kubernetes
- CI/CD and DevSecOps
- React/Angular knowledge
- ML/MLflow/MLOps fundamentals
- Knowledge graphs
- Agentic AI / multi-agent concepts
Benefits
Mitarbeiterrabatte möglich
Gesundheitsmaßnahmen
Mitarbeiterhandy möglich
Essenszulagen
Betriebliche Altersversorgung
Hybrides Arbeiten möglich
Mobilitätsangebote
Mitarbeiter Events
Coaching
Flexible Arbeitszeit möglich
Parkplatz
Betriebsarzt
Gute Anbindung
Barrierefreiheit
Kinderbetreuung
Kantine, Café
Kontakt Mercedes-Benz Research and Development India Private Limited
Brigade Tech Gardens, Katha No. 119560037 BengaluruDetails zum Standort
Jacob Cyril E-Mail:
[email protected]
📌 AI Engineer- AI Native Engineering (Bengaluru)
🏢 Mercedes Benz Group
📍 Bengaluru